Financial Model Risk Management Lead

Overview

This role sits within Enterprise Risk & Internal Audit and supports the organization’s risk management efforts by validating financial and analytics quantitative models. The Model Risk Management (MRM) team serves as a second line of defense, establishing and overseeing a model risk management framework to identify, quantify, monitor, mitigate, and report on model risk.

Responsibilities

• Perform independent challenges of financial and analytics quantitative models, including ALM, allowance/loss forecasting, loan transition models (LTM), corporate financial planning models, take-up and engagement models, and related decision-support analytics through rigorous validation and ongoing monitoring
• Lead end-to-end validation engagements on high-complexity, high-criticality models
• Identify model weaknesses, limitations, and opportunities for improvement; communicate findings clearly to both technical and non-technical stakeholders
• Collaborate with model owners and stakeholders across Finance, Quantitative Research, and Growth Analytics to remediate validation findings and strengthen model governance
• Partner cross-functionally to implement and maintain the organization’s MRM framework
• Partner with Internal Audit, Internal Controls, Accounting, and Compliance to ensure timely resolution of audit, regulatory, and examiner requests

Requirements

• 4–6 years of professional experience in related technical areas such as model development, model validation, quantitative finance, or data analytics, with meaningful exposure to financial and/or analytics model validation
• Deep and broad knowledge of corporate finance, treasury, ALM, and/or actuarial/statistical forecasting
• Experience in credit underwriting or credit risk management is a plus
• Proven ability to work with scripting languages (e.g., Python) and large-scale datasets (e.g., SQL)
• Comfort reviewing models built in Excel, Python, Databricks, or similar environments
• Experience with statistical modeling, time-series forecasting, simulation, and/or machine learning techniques as applied to finance and analytics use cases
• BS, MS, or PhD in a quantitative field such as Quantitative Finance, Financial Engineering, Mathematics, Statistics, Economics, Computer Science, or Data Science
• Detail-oriented and intellectually curious about data, models, and business context; skilled at critical thinking and structured problem-solving
• Extraordinary interpersonal and verbal/written communication skills, including the ability to influence model owners, present to senior stakeholders, and navigate cross-functional remediation

Compensation & Benefits

• Pay Grade: M
• Equity Grade: 8
• Employees new to the organization typically come in at the start of the pay range.
• Base pay range (CA, WA, NY, NJ, CT) per year: $185,000 - $245,000
• Base pay range (all other U.S. states) per year: $164,000 - $224,000
• Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits including 100% subsidized medical coverage, dental and vision for you and your dependents.
• Health coverage at no cost: 100% of premiums for employees and their dependents
• Spending stipends: Monthly stipends support your tech setup and health and wellness options
• Time off to recharge: Flexible time off and generous holiday calendars
• Own a piece of what you build: Employee Stock Purchase Plan (ESPP) to buy company stock at a discount

Location

Remote-first with flexibility built in. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

For positions based in San Francisco or Los Angeles: the organization considers qualified applicants with arrest and conviction records, as required by law.